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Xu et al. (2012) pay attention to the Chinese stock market in 2010, choosing variables such as industry fixed effect, event type, disclosure level and modernization rate.
This work introduces a new information-theoretic methodology for choosing variables and their time lags in a prediction setting, particularly when neural networks are used in non-linear modeling.
Furthermore, it is recommended to exercise parsimony in choosing variables [ 1, 20, 28, 33, 39].
Our first goal is to develop a Boolean model based on the minimal model approach for choosing variables and parameters used by Santillán et al. (2007).
To evaluate this possibility, we compared the performance of our 13-varible model to models formed by choosing variables randomly from the 377 variables evaluated on the cohort we studied (Additional File 5).
The significant level was set at P < 0.05 (two tailed) in all analyses, but in choosing variables to be included in the multiple logistic regression analysis, a cutoff of 0.1 was applied in order to include more potential covariates.
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Youden and Steiner's robustness test, involving seven chosen variables, showed that the method is robust.
The ℘ and ℓ terms are arbitrarily chosen variables used to simplify the BER expression.
The chosen variables derived from our review of the DEA literature on seaports.
Once a subset of variables is selected, a basic PNN is developed on the chosen variables for future applications.
The chosen variables are reaction time, initial catalyst percent and methanol:oil ratio, while the response is the biodiesel yield.
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